NDLI: AR+ noise versus AR and ARMA models in SHM-oriented identification

Content Provider	IEEE Xplore Digital Library
Author	Guidorzi, R. Diversi, R. Vincenzi, L. Simioli, V.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr., Electron. & Inf. Eng. (DEI), Univ. of Bologna, Bologna, Italy (Guidorzi, R.; Diversi, R.) \|\| Teleco SpA, Lugo, Italy (Simioli, V.) \|\| Dept. of Mech. & Civil Eng., Univ. of Modena & Reggio Emilia, Modena, Italy (Vincenzi, L.)
Abstract	The most common approach in Structural Health Monitoring (SHM) consists in performing accelerometric measures of the response of the monitored structures to natural or artificial stimuli (e.g. wind, urban traffic, seismic events etc.) and in modeling the dynamic behavior of the structure on the basis of these measures. The models can be used, in particular, to extract and compare the main modes i.e. the main resonant frequencies and in comparing these frequencies with those concerning the initial state of integrity of the building. This paper compares the results given by traditional AR and ARMA models with those offered by AR+noise models where an additive observation error is considered and shows that these models can offer some advantages in SHM applications in that describe more accurately the stochastic context of the process. The comparisons have been performed on two different sets of data: the first one has been collected on an industrial building in occasion of an heavy seismic event whereas the second one has been collected on a medieval tower excited by urban traffic.
Starting Page	809
Ending Page	814
File Size	366168
Page Count	6
File Format	PDF
ISBN	9781479999361
DOI	10.1109/MED.2015.7158845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-16
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models AR+noise models identification Computational modeling Noise Buildings SHM Data models Sensors Mathematical model
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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